{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T11:37:51Z","timestamp":1770291471759,"version":"3.49.0"},"reference-count":45,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2023,11,10]],"date-time":"2023-11-10T00:00:00Z","timestamp":1699574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2022YFB2503302"],"award-info":[{"award-number":["2022YFB2503302"]}]},{"name":"National Key Research and Development Program of China","award":["52225212"],"award-info":[{"award-number":["52225212"]}]},{"name":"National Key Research and Development Program of China","award":["U20A20333"],"award-info":[{"award-number":["U20A20333"]}]},{"name":"National Key Research and Development Program of China","award":["BE2020083-3"],"award-info":[{"award-number":["BE2020083-3"]}]},{"name":"National Natural Science Foundation of China","award":["2022YFB2503302"],"award-info":[{"award-number":["2022YFB2503302"]}]},{"name":"National Natural Science Foundation of China","award":["52225212"],"award-info":[{"award-number":["52225212"]}]},{"name":"National Natural Science Foundation of China","award":["U20A20333"],"award-info":[{"award-number":["U20A20333"]}]},{"name":"National Natural Science Foundation of China","award":["BE2020083-3"],"award-info":[{"award-number":["BE2020083-3"]}]},{"name":"Key Research and Development Program of Jiangsu Province","award":["2022YFB2503302"],"award-info":[{"award-number":["2022YFB2503302"]}]},{"name":"Key Research and Development Program of Jiangsu Province","award":["52225212"],"award-info":[{"award-number":["52225212"]}]},{"name":"Key Research and Development Program of Jiangsu Province","award":["U20A20333"],"award-info":[{"award-number":["U20A20333"]}]},{"name":"Key Research and Development Program of Jiangsu Province","award":["BE2020083-3"],"award-info":[{"award-number":["BE2020083-3"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As a fundamental computer vision task, instance segmentation is widely used in the field of autonomous driving because it can perform both instance-level distinction and pixel-level segmentation. We propose CompleteInst based on QueryInst as a solution to the problems of missed detection with a network structure designed from the feature level and the instance level. At the feature level, we propose Global Pyramid Networks (GPN) to collect global information of missed instances. Then, we introduce the semantic branch to complete the semantic features of the missed instances. At the instance level, we implement the query-based optimal transport assignment (OTA-Query) sample allocation strategy which enhances the quality of positive samples of missed instances. Both the semantic branch and OTA-Query are parallel, meaning that there is no interference between stages, and they are compatible with the parallel supervision mechanism of QueryInst. We also compare their performance to that of non-parallel structures, highlighting the superiority of the proposed parallel structure. Experiments were conducted on the Cityscapes and COCO dataset, and the recall of CompleteInst reached 56.7% and 54.2%, a 3.5% and 3.2% improvement over the baseline, outperforming other methods.<\/jats:p>","DOI":"10.3390\/s23229102","type":"journal-article","created":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T02:46:47Z","timestamp":1699843607000},"page":"9102","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["CompleteInst: An Efficient Instance Segmentation Network for Missed Detection Scene of Autonomous Driving"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9136-8091","authenticated-orcid":false,"given":"Hai","family":"Wang","sequence":"first","affiliation":[{"name":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7733-8217","authenticated-orcid":false,"given":"Shilin","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Chen","sequence":"additional","affiliation":[{"name":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yicheng","family":"Li","sequence":"additional","affiliation":[{"name":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4677-854X","authenticated-orcid":false,"given":"Tong","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Automobile and Traffic Engineering, Jiangsu University of Technology, Changzhou 213001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, G., Peng, Y., and Wang, H. 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